Three publicly available tumor databases, including TNMplot (differential gene expression analysis in tumor, healthy control and metastatic tissues, https://tnmplot.com/), TCGA (https://portal.gdc.cancer.gov/) and ICGC (https://dcc.icgc.org/), were used for the investigation of NCAPD2 expression in liver cancer. From the TNMplot database (15), which uses gene chip or RNA-sequencing (RNA-seq) data to display the analysis of specific genes in selected tissue types, data from 379 paracancerous liver tissues and 806 primary liver cancer tissues were collected. TCGA-Genotype-Tissue Expression Project database was used to identify 50 paracancerous liver tissues and 374 liver cancer tissues. The ICGC database was used to identify 202 paracancerous liver tissues and 240 liver cancer tissues. The Human Protein Atlas (HPA, https://www.proteinatlas.org/) is a public database that was used to obtain proteome expression information of genes from 44 paracancerous control tissues and 18 tumor tissues. The HPA was used to investigate NCAPD2 protein expression in patients with liver cancer.

Clinical specimens were fixed in 10% neutral formalin at room temperature for 12-24 h and embedded in paraffin. A total of 33 formalin-fixed paraffin-embedded (FFPE) specimens, including 20 liver cancer and 13 paired adjacent non-cancerous liver samples, were collected for validation from the Department of Pathology, Taihe Hospital (Shiyan, China) between July and October 2023. The inclusion criteria of the clinical specimens were: i) Confirmation of liver cancer diagnosis by senior pathologists using tumor tissues from patients that did not undergo preoperative radiotherapy or chemotherapy; and ii) patients were free of other diseases, or their medical history revealed no other diseases apart from liver cancer.

IHC detection of all FFPE slides was conducted using EliVision methods according to the manufacturers' instructions. Specifically, all 3-µm FFPE sections were dewaxed with xylene and rehydrated with graded ethanol. After antigen repair with EDTA (pH 9.0) in a pressure cooker for 4 min, endogenous peroxidase activity was blocked with 3% hydrogen peroxide in methanol for 10 min at room temperature. The slides were then incubated with primary antibodies (Table SI) at 37°C for 1 h, were washed three times with PBS (3 min/wash), and were incubated with horseradish peroxidase (HRP)-labeled secondary antibody (cat. no. KIT-9923; Fuzhou Maixin Biotechnology Development Co., Ltd.) at 37°C for 0.5 h. The nuclei were stained with hematoxylin for 30 sec and the sections were washed with water for bluing after 0.5% HCI-ethanol differentiation for 3 sec. Finally, chromogen detection was performed using DAB Plus Kit (cat. no. DAB-2032; Fuzhou Maixin Biotechnology Development Co., Ltd.) at room temperature for 10 min.

All IHC staining results were scanned and scored by at least two experienced pathologists. IHC staining of NCPAD2⁺ cells was detected using light microscopy (magnification, ×200 or ×100) and these cells were graded based on quantity and intensity scores. Specifically, the quantity scoring criteria were: 0, absent; 1, ≤10%; 2, 11-50%; 3, 51-75%; 4, >75% and the intensity scoring criteria were: 0, no staining; 1, light yellow; 2, brownish yellow; 3, dark brown. The quantity and intensity scores were multiplied to yield an overall score ranging between 0 and 12. The percentage of Ki67⁺ cells was calculated as the percentage of Ki67⁺ cells to all cells in the field of view at low magnification (×200).

Additionally, total RNA was extracted from FFPE slides using the RNeasy FFPE kit (Qiagen GmbH) and total RNA was then used to synthesize first-strand cDNA using the First Strand cDNA Synthesis kit (Vazyme Biotech Co., Ltd.); these steps were performed according to the manufacturers' protocols. qPCR was carried out in an ABI Prism 7000 analyzer (Applied Biosystems; Thermo Fisher Scientific, Inc.) using Green Mix SYBR (Vazyme Biotech Co., Ltd.) and specific primers (Table SII) to determine mRNA expression. The thermocycling conditions were as follows: initial denaturation at 120 sec for 95°C, followed by 40 cycles at 95°C for 15 sec, 58°C for 15 sec and 72°C for 30 sec. GAPDH was used as an endogenous control. All experiments were performed in triplicate. The relative mRNA expression levels in liver cancer samples were determined using the 2^−ΔΔCq method (16). The primers were obtained from Sangon Biotech Co., Ltd.

The association between NCAPD2 expression and the clinicopathological parameters of patients with liver cancer was assessed using TCGA-liver cancer data. All patients with liver cancer were divided into two subgroups based on median cut-off values; the high NCAPD2 expression (n=187) and the low NCAPD2 expression (n=187) groups. The distribution of NCAPD2 expression in liver cancer in terms of age, pathological TNM (pTNM) stage, histological grades and survival status was plotted in an Sankey diagram. RNA-sequencing expression profiles and corresponding clinical information for liver cancer were downloaded from TCGA dataset. The package 'ggalluvial' of R software (version 4.2.1) was used to build Sankey diagram (17). Subsequently, the prognostic analysis of NCAPD2 expression in liver cancer was analyzed including overall survival (OS) or disease-specific survival (DSS) data from TCGA or the ICGC datasets based on Kaplan-Meier and log-rank test. Furthermore, univariate Cox (uni-cox) and multivariate Cox (multi-cox) regression analyses were applied to investigate the relationship between NCAPD2 expression and other clinicopathological signatures in TCGA-liver cancer data.

Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) assesses mesenchymal and immune cells in malignant tumors using gene expression data. The algorithm scores specific sets of genes by GSEA to obtain the stromal and the immune scores of the tumor sample, and these two scores are added together to obtain the ESTIMATE score, which can be used to estimate tumor purity. With the ESTIMATE algorithm, stromal and immune scores can be obtained for every sample, and then the tumor samples can be classified into high- and low-expression subgroups based on these scores, facilitating subsequent bioinformatics analysis and research. Specifically, immune infiltration analyses of the ESTIMATE algorithm, including stromal and immune scores, and the ESTIMATE score were conducted via the 'estimate' (version 1.0.13) package (18) in R (version 4.2.1) software (https://www.r-project.org/). Furthermore, the evaluation of immune cell abundance was derived from the GSEA algorithm provided in the R package 'GSVA' (version 1.46.0) (19). For GSEA, the R package GSVA (20,21) was used to investigate the underlying molecular mechanisms of NCAPD2 in TCGA-liver cancer data. Spearman's correlation coefficient was used to denote the correlation between genes and pathway scores. Thresholds were set at Spearman's correlation coefficient, r_s>0.5. P<0.05 was considered to indicate a statistically significant difference.

Integrated iMMune profiling of large adaptive CANcer patient cohorts (IMMUcan), an online service platform established by a team of researchers from the Institute of Research Saint-Louis (Paris, France), collects single-cell sequencing data of >56 cancer types worldwide, and aims to create and integrate the clinical, cellular and molecular profile of different tumor types and the tumor immune microenvironment (22). The IMMUcan database provides detailed clinical annotations that link cell types and gene expression patterns to specific clinical patterns. It also provides extensive functionality for analyzing multiple datasets. The single-cell RNA-seq datasets GSE140228 (23) and GSE112271 (24) from the Gene Expression Omnibus dataset (https://www.ncbi.nlm.nih.gov/geo/; Table SIII) were used to characterize NCAPD2 expression in different cell clusters from liver cancer.

NCAPD2 expression was assessed in the liver cancer cell lines Huh7 (cat. no. CL-0120; Procell Life Science & Technology Co. Ltd.), MHCC-97H (cat. no. TCH-C258; HyCyte), HepG2 (cat. no. CL-0103; Procell Life Science & Technology Co. Ltd.) and LM3 (cat. no. TCH-C456; HyCyte). All cell lines used in the current study were authenticated using short tandem repeat profiling. In vitro assays involving HepG2 cells with small interfering RNA (siRNA)-induced NCAPD2 knockdown using si-NCAPD2, or Huh7 cells with pcDNA-NCAPD2 plasmid-induced NCAPD2 overexpression were performed to discover the molecular mechanisms of NCAPD2 in liver cancer.

The liver cancer cell lines HepG2, Huh7, MHCC-97H and LM3 were cultured in basic DMEM (cat. no. C11995500BT; Gibco; Thermo Fisher Scientific, Inc.) supplemented with 10% fetal bovine serum (Gibco; Thermo Fisher Scientific, Inc.) at 37°C and 5% CO_2. The culture medium was replaced every 2-3 days until cell density reached >90% for passaging, and cells in the logarithmic growth phase were used for RT-qPCR and subsequent experiments.

When cell density reached ~70%, 50 nmol plasmids or 50 nmol siRNAs were transfected into liver cancer cells using Lipofectamine^® 3000 (Invitrogen; Thermo Fisher Scientific, Inc.) according to the manufacturer's instructions. Huh7 cells were transfected with the NCAPD2 overexpression plasmid pcDNA3.1-NCAPD2 (Zhuhai DL Biotech Co., Ltd.), and pcDNA3.1 was used as a control. HepG2 cells were transfected with si-NCAPD2 (Guangzhou Ribobio Co., Ltd.; Table SII), and si-negative control (NC) was used as a control. All cell line experiments were performed at 37°C. The culture medium was refreshed 6 h after transfection, and most other experiments (RT-qPCR, cell proliferation, flow cytometry, cell invasion, cell migration experiments, etc.) were carried out 24 h post-transfection, with the exception of western blotting, which was carried out 48 h post-transfection. The experiments were performed in triplicate.

Total RNA was extracted from cell lines using TRIzol^® reagent (Invitrogen; Thermo Fisher Scientific, Inc.), according to the manufacturer's instructions. Total RNA was used to synthesize first-strand cDNA using the First Strand cDNA Synthesis kit and qPCR was carried out as aforementioned.

A total of 5,000 cells/well were cultured in 96-well plates, and MTT reagent (20 µl/well; Sigma-Aldrich; Merck KGaA) was added at 24, 48 and 72 h in the dark. The supernatant was removed after 4 h of incubation and DMSO (150 µl/well; Sigma-Aldrich; Merck KGaA) was added. Optical density was measured at 495 nm.

Cells were cultured in 12-well plates for 24 h, and were then digested with trypsin and counted. Cell suspensions were prepared using serum-free medium to ensure cell density was 5×10⁴ cells/well and were seeded into Transwell cell culture chambers (24-well; pore size, 8 µm; cat. no. 3422; Corning, Inc.). For the cell invasion experiments, Matrigel (cat. no. 356234; Corning, Inc.) was diluted and spread evenly in the upper chamber, and was incubated at 37°C overnight. Subsequently, 200 µl cell suspension was added to the upper chamber, 600 µl DMEM supplemented with 10% fetal bovine serum was added to the lower chamber, and the cells were incubated at 37°C for 24 h, after which, images were captured. For the cell migration experiments, the same steps were performed as for the invasion assay; however, Matrigel-free chambers were used. Subsequently, the chambers were fixed with anhydrous methanol for 30 min, stained with 0.1% crystal violet for 20 min at room temperature and finally washed with double-distilled water three times. Images were captured under a light microscope after the chambers were dried to observe cell migration and invasion.

Cells were cultured in 6-well plates for 24 h to achieve uniform coverage of the entire culture plate, and were then scratched vertically with a 200-µl pipette tip, washed three times with PBS and cultured in serum-free medium. Cell migration was observed at 0 and 48 h; images of the cells were captured under a light microscope and cell migration was analyzed using ImageJ (version 1.8.0; National Institutes of Health). Cell migration rate (%)=(0 h scratch area −48 h scratch area)/0 h scratch area ×100.

For the cell cycle experiments, cells were digested with 0.25% trypsin-EDTA solution, centrifuged for 100 × g at room temperature for 5 min, and the cell precipitates were collected and washed twice with PBS. Subsequently, 1.0×10⁴ cells were fixed with 70% ethanol at 4°C overnight, and were then incubated with 100 mg/l RNase A and 50 mg/l PI solution (Beyotime Institute of Biotechnology) at 37°C for 30 min in the dark. Cell cycle progression was assessed using a flow cytometer (FACSCalibur; BD Biosciences), and the proportion of cells in each phase of the cell cycle was analyzed using FlowJo7.6 software (FlowJo LLC).

For the cell apoptosis assay, the same trypsin digestion was performed as for cell cycle experiments; subsequently, the precipitate was collected and 1.0×10⁴ cells were washed twice with PBS and resuspended in 100 μl PBS. Cells were then incubated with 8 μl FITC staining solution for 15 min at room temperature and 2 μl PI staining solution for 5 min at room temperature in the dark, according to the instructions of the Annexin V-FITC/PI Apoptosis Double Staining kit (cat. no. 556547; BD Biosciences). Finally, the apoptotic rate was analyzed by flow cytometry (FACSCalibur) using FlowJo7.6 software.

Cells were lysed using RIPA lysis buffer (Beyotime Institute of Biotechnology) and were placed on ice for 30 min before the cell lysates were centrifuged at 4°C for 15 min. Protein concentration was determined using the BCA assay (Beyotime Institute of Biotechnology). Subsequently, proteins were incubated for 10 min in loading buffer, and 30 μg protein/lane was separated by SDS-PAGE on 10% gels and transferred to PVDF membranes (MilliporeSigma). The membranes were incubated with 5% skimmed milk powder at room temperature for 2 h, and TBS-1% Tween-20 (TBST; neoFroxx GmbH) was used to wash the membrane three times (10 min/wash). Finally, the membranes were incubated with diluted primary antibodies (Table SI) overnight at 4°C, washed three times with TBST and then incubated with HRP-linked secondary antibodies (1:5,000; anti-rabbit/mouse IgG; cat. nos. 7074s and 7076s; Cell Signaling Technology, Inc.) for 2 h at room temperature. The blots were visualized on a gel imager (Bio-Rad Laboratories, Inc.) using an enhanced chemiluminescence substrate kit (cat. no. BL523B; Biosharp Life Sciences).

All statistical analyses were performed using GraphPad Prism (version 8.0; Dotmatics). Data are expressed as the mean ± SD and all in vitro experiments were performed in triplicate. Paired Student's t-test was used to determine the significance of differences between two paired groups. Unpaired Student's t-test was used to determine the significance of differences between two independent groups. To compare multiple groups, one-way ANOVA followed by Bonferroni test was used. In addition, the χ² test, Fisher's exact test and log-rank test were used, and non-parametric data were analyzed using Mann-Whitney U test and Spearman's correlation coefficient. P<0.05 was considered to indicate a statistically significant difference.

Based on the TNMplot, TCGA and ICGC databases, bioinformatics analyses revealed that the mRNA expression levels of NCAPD2 were upregulated in liver cancer tissues compared with those in healthy control liver tissues (Fig. 1A-D). Furthermore, NCAPD2 mRNA expression was upregulated in liver cancer tissues compared with in paired healthy control tissues (Fig. 1C). In terms of NCAPD2 protein expression, the HPA dataset indicated that NCAPD2 was markedly upregulated in liver cancer tissues compared with in healthy control tissues (Fig. 1E).

For the validation of NCAPD2 expression in patients with liver cancer, 20 liver cancer tissues and 13 adjacent non-cancerous samples were collected for IHC. The results suggested that NCAPD2 was significantly higher in liver cancer tissues than in adjacent non-cancerous tissues in terms of protein (Fig. 2A and B) and mRNA expression levels (Fig. 2C).

As a cell proliferation index, Ki67 was used to investigate the relationship between NCAPD2 expression and Ki67⁺ cells in liver cancer. It was suggested that NCAPD2 expression, namely NCAPD2 IHC score, was positively correlated with the proportion of Ki67⁺ cells (Fig. 3A and B). In addition, based on TCGA-liver cancer data, NCAPD2 expression was positively correlated with the expression of MKI67, the gene symbol of Ki67 (Fig. 3C).

The association of NCAPD2 and clinicopathological parameters in liver cancer revealed that NCAPD2 expression was significantly associated with age, pTNM stage (especially T stage), histological grade and α-fetoprotein (AFP; P<0.001), but not with sex, BMI, residual tumor and Ishak fibrosis score (25) (Table SIV). In addition, an alluvial diagram showed the distribution of NCAPD2 expression in terms of age, pTNM stage, histological grade and survival status (Fig. 4A). It suggested that NCAPD2 expression was related to age, pTNM stage, histological grade and survival status in liver cancer. Furthermore, NCAPD2 expression was upregulated in patients with advanced pTNM stage or advanced histological grade liver cancer, or in those with higher AFP levels (>400 ng/ml) compared with in the control subgroups (Fig. 4B-D). Subsequently, the prognostic analysis revealed that upregulation of NCAPD2 was associated with poor OS and DSS based on TCGA data (Fig. 4E and F) or ICGC data (Fig. 4G). The uni-cox and multi-cox regression analyses indicated that NCAPD2 expression was strongly associated with prognosis, and may serve as an independent prognostic marker of OS in patients with liver cancer (Table SV). Furthermore, among the common types of gene mutations in liver cancer based on TCGA dataset, including TP53 and CTNNB1 mutations, the analysis showed that NCAPD2 expression was increased in TP53 mutant (mut) compared with in TP53 wild-type (wt) liver cancer (Fig. 4H). The expression of NCAPD2 was not associated with CTNNB1 mutation (Fig. 4I).

Immune infiltration assays suggested that the stromal score was significantly lower in the high NCAPD2 expression group compared with that in the low NCAPD2 expression group, but no difference was observed for the immune score or ESTIMATE score (Fig. 5A). Subsequently, the GSEA algorithm revealed that the abundance of most immune cells was not related to differences in the expression of NCAPD2, with the exception of dendritic cells and T helper (Th) cells (especially Th2 and Th17 cells) (Fig. 5B). Moreover, the GSEA asserted that liver cancer with high NCAPD2 expression was mostly enriched in the phosphatidylinositol 3-kinase (PI3K)-Akt-mammalian target of rapamycin (mTOR) signaling pathway, the tumor proliferation signature, the G₂/M checkpoint of the cell cycle and Myc signal targets (Fig. 5C). In the GSE140228 dataset, the high expression subgroup of NCAPD2 was mainly enriched in the cell population in the cell cycling state (Fig. 5D); the GSE112271 dataset denoted that NCAPD2 was mainly expressed in the malignant cell population (Fig. 5E).

NCAPD2 expression was assessed in the liver cancer cell lines Huh7, MHCC-97H, HepG2 and LM3. Among these four liver cancer cell lines, the mRNA and protein expression levels of NCAPD2 were highest in HepG2 cells and lowest in Huh7 cells (Fig. 6A and B). Thus, HepG2 cells were selected for siRNA experiments and Huh7 cells were selected for overexpression experiments to further investigate the biological roles of NCAPD2 in liver cancer. Notably, the mRNA and protein expression levels of NCAPD2 were significantly inhibited in HepG2 cells transfected with si-NCAPD2 compared with those transfected with si-NC (Fig. 6C and D). By contrast, the mRNA and protein expression levels of NCAPD2 were significantly upregulated in Huh7 cells transfected with pcDNA-NCAPD2 compared with those transfected with pcDNA3.1. Specifically, NCAPD2 knockdown significantly inhibited the proliferation (Fig. 6E), invasion and migration (Fig. 6G and I) of HepG2 cells transfected with si-NCAPD2 compared with those transfected with si-NC. Flow cytometry showed that NCAPD2 knockdown significantly enhanced the apoptosis of HepG2 cells (8.88 vs. 11.1%; Fig. 6K). By contrast, overexpression of NCAPD2 increased the proliferation (Fig. 6F), invasion and migration (Fig. 6H and J) of Huh7 cells transfected with pcDNA-NCAPD2 compared with those transfected with pcDNA3.1. Flow cytometry also showed that NCAPD2 overexpression impeded the apoptosis of Huh7 cells (10.95 vs. 6.76%; Fig. 6L).

Flow cytometry revealed that knockdown of NCAPD2 inhibited the cell cycle at the G₂/M-phase transition and enhanced G₀/G₁-phase transition in HepG2 cells (Fig. 7A), whereas overexpression of NCAPD2 boosted the cell cycle at the G₂/M-phase transition in Huh7 cells (Fig. 7B). Western blotting revealed that knockdown of NCAPD2 expression suppressed the expression levels of c-Myc; affected the expression levels of EMT-related proteins, including upregulation of E-cadherin, and downregulation of N-cadherin and vimentin; and reduced the phosphorylation of mTOR, PI3K and Akt in HepG2 cells. By contrast, NCAPD2 overexpression enhanced the expression levels of c-Myc; activated the EMT via altering the expression levels of the related proteins, including downregulation of E-cadherin, and upregulation N-cadherin and vimentin; and increased the expression levels of phosphorylated (p)-mTOR, p-PI3K and p-Akt in Huh7 cells (Fig. 7C).